Intelligent noise reduction refrigerator and control method

Abstract

The application provides a kind of intelligent noise reduction refrigerator and control method, the refrigerator includes: acquisition module, the acquisition module is set on the cabinet, is configured to: acquisition contrast data;The contrast data includes: CSI, refrigerator door switch, temperature and humidity, light intensity, audio data;Data analysis module, the data analysis module is connected with the acquisition module, the data analysis module is electrically connected with compressor, fan;The data analysis module is configured to: obtain the contrast data whether greater than data threshold;If yes, then control refrigerator to run in noise reduction mode;When the refrigerator runs in noise reduction mode, the compressor, fan speed is reduced to preset value, to solve the current through the installation of sound insulation layer noise reduction refrigerator can cause poor heat dissipation of refrigerator, heat generated by refrigeration system when working will be blocked by sound insulation layer, difficult to dissipate, resulting in the refrigeration system of refrigerator will be damaged because of running overheating, cause refrigerator function is damaged.

Description

Technical Field

[0001] This application relates to the field of refrigeration equipment technology, and in particular to an intelligent noise-reducing refrigerator and its control method. Background Technology

[0002] As people's living standards improve, refrigerators have become a necessity in almost every household. When a refrigerator is working, the compressor and cooling fan operate at high speeds for extended periods, causing it to emit a significant amount of noise that is difficult to mask.

[0003] To mask noise, smart refrigerators typically have sound insulation or vacuum layers installed inside or outside. These sound insulation layers are usually made of sound-absorbing foam boards or cotton. The noise generated by the refrigeration system is absorbed through the spaces within the foam pores or sound-absorbing cotton, thus achieving noise reduction.

[0004] However, installing a sound insulation layer can lead to poor heat dissipation in the refrigerator. The heat generated by the refrigeration system during operation will be blocked by the sound insulation layer and will be difficult to dissipate, causing the refrigeration system to be damaged due to overheating and resulting in impaired refrigerator function. Summary of the Invention

[0005] This application provides an intelligent noise-reducing refrigerator and control method to solve the technical problem that current noise-reducing refrigerators that install sound insulation layers have poor heat dissipation. The heat generated by the refrigeration system during operation is blocked by the sound insulation layer and is difficult to dissipate, which leads to damage to the refrigeration system due to overheating and impaired refrigerator function.

[0006] The first aspect of this application provides a smart noise-reducing refrigerator, comprising:

[0007] The data acquisition module, which is mounted on the housing, is configured as follows:

[0008] Collect and compare data; the comparison data includes: CSI, refrigerator door open / close, temperature and humidity, light intensity, and audio data;

[0009] The data analysis module is communicatively connected to the acquisition module and electrically connected to the compressor and fan. The data analysis module is configured as follows:

[0010] Determine whether the comparison data is greater than a data threshold;

[0011] If so, the refrigerator is controlled to operate in noise reduction mode; when the refrigerator is operating in noise reduction mode, the speed of the compressor and fan is reduced to a preset value.

[0012] In some embodiments, the data analysis module is communicatively connected to the router, and a first detection area is formed between the data analysis module and the router;

[0013] The acquisition module is further configured as follows:

[0014] Collect CSI data within the first detection area;

[0015] The data analysis module is further configured as follows:

[0016] Based on the CSI data, a human activity value is calculated. If the human activity value is greater than the human activity threshold, the refrigerator is controlled to operate in a noise reduction mode.

[0017] In some embodiments, the first detection area is the area above a preset height between the data analysis module and the router.

[0018] In some embodiments, the data analysis module is further configured to:

[0019] Based on the refrigerator door opening / closing data, determine whether the refrigerator door is open;

[0020] If the refrigerator door is opened, the refrigerator will be controlled to operate in noise reduction mode.

[0021] In some embodiments, the acquisition module is further configured to:

[0022] Collect temperature and humidity values ​​inside the chamber;

[0023] The data analysis module is further configured as follows:

[0024] Based on the temperature value and the humidity value, determine whether the fluctuation value of the temperature value or the humidity value within a first preset time period is greater than the temperature value threshold or the humidity value threshold.

[0025] If so, the refrigerator is controlled to operate in noise reduction mode.

[0026] In some embodiments, the acquisition module is further configured to:

[0027] The light intensity within the second detection area is collected; the second detection area is the detection area of ​​the light intensity sensor, which is located outside the enclosure.

[0028] The data analysis module is further configured as follows:

[0029] Based on the light intensity, determine whether the fluctuation value of the light intensity within a second preset time period is greater than the light intensity threshold.

[0030] If so, the refrigerator is controlled to operate in noise reduction mode.

[0031] In some embodiments, the data analysis module is further configured to:

[0032] Based on the audio data, obtain the sound intensity outside the enclosure;

[0033] Based on the sound intensity, determine whether the sound intensity is greater than a sound intensity threshold;

[0034] If so, the refrigerator is controlled to operate in noise reduction mode.

[0035] In some embodiments, the data analysis module is further configured to:

[0036] Obtain module start / stop commands;

[0037] According to the module start / stop command, the noise reduction mode is controlled to turn off according to the set time.

[0038] In some embodiments, the data analysis module is further configured to:

[0039] The comparison data is preprocessed; the preprocessing operations include: noise reduction, filtering, and standardization.

[0040] Obtain the packet loss rate and signal strength of CSI data;

[0041] If the packet loss rate or the signal strength of the CSI data is less than the packet loss rate threshold or the signal strength threshold, then the CSI data will be deleted.

[0042] The second aspect of this application provides a control method for an intelligent noise-reducing refrigerator, applied to an intelligent noise-reducing refrigerator as described in any one of the first aspects above, comprising:

[0043] Collect and compare data; the comparison data includes: CSI, refrigerator door open / close, temperature and humidity, light intensity, and audio data;

[0044] Determine whether the comparison data is greater than a data threshold;

[0045] If so, the refrigerator is controlled to operate in noise reduction mode; when the refrigerator is operating in noise reduction mode, the compressor and fan speeds are reduced to preset values.

[0046] This application provides an intelligent noise-reducing refrigerator and its control method. The refrigerator includes: a data acquisition module disposed on the refrigerator body and configured to: acquire comparison data; the comparison data includes: CSI, refrigerator door open / close, temperature and humidity, light intensity, and audio data; and a data analysis module communicatively connected to the data acquisition module and electrically connected to the compressor and fan; the data analysis module is configured to: determine whether the comparison data is greater than a data threshold; if so, control the refrigerator to operate in noise reduction mode; when the refrigerator operates in noise reduction mode, the compressor and fan speeds are reduced to preset values, so that the noise-reducing refrigerator can complete the noise reduction function of the refrigerator through multimodal data. Attached Figure Description

[0047] To more clearly illustrate the technical solution of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0048] Figure 1 This is a schematic diagram of the noise reduction module of the intelligent noise reduction refrigerator in this application;

[0049] Figure 2 A flowchart illustrating the noise reduction function of the intelligent noise-reducing refrigerator in this application.

[0050] Explanation of reference numerals in the attached figures:

[0051] 1-Data acquisition module; 2-Data analysis module. Detailed Implementation

[0052] To enable those skilled in the art to better understand the technical solutions in this application, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this application.

[0053] In some technologies, installing sound insulation layers in refrigerators can lead to poor heat dissipation. The heat generated by the refrigeration system during operation is blocked by the sound insulation layer, making it difficult to dissipate. This can cause the refrigeration system to overheat and be damaged, resulting in impaired refrigerator functionality. To address this technical problem, this application provides an intelligent noise-reducing refrigerator and its control method. The intelligent noise-reducing refrigerator and control method are described below:

[0054] Depend on Figure 1As can be seen, the first aspect of this application provides an intelligent noise-reducing refrigerator, including: a data acquisition module 1, which is disposed on the refrigerator body and configured to: acquire comparison data; the comparison data includes: CSI, refrigerator door opening / closing, temperature and humidity, light intensity, and audio data; Channel State Information (CSI) includes specific indicators, such as carrier signal strength, amplitude, phase, and signal delay; the above indicators reveal the signal scattering, reflection, and power attenuation phenomena of the carrier as the transmission distance changes, and can be used to measure the channel state of wireless networks in Wi-Fi communication. By analyzing and studying the changes in CSI, the changes in the physical environment that cause the changes in channel state can be inferred, that is, non-contact intelligent sensing can be achieved. CSI is extremely sensitive to environmental changes. In addition to sensing environmental changes caused by large movements such as walking and running of people or animals, it can also capture subtle movements caused by small movements such as breathing and chewing of people or animals in static environments. The CSI data is used to obtain information such as signal scattering, environmental attenuation, and distance attenuation.

[0055] Data analysis module 2 is communicatively connected to acquisition module 1 and electrically connected to the compressor and fan. Data analysis module 2 is configured to: determine whether the compared data exceeds a data threshold; if so, control the refrigerator to operate in noise reduction mode; when the refrigerator operates in noise reduction mode, the compressor and fan speeds are reduced to preset values. By acquiring the refrigerator's multimodal data (CSI, refrigerator door open / closed status, temperature and humidity, light intensity, and audio data) in real time, it can determine whether there are people around the refrigerator, activate the refrigerator's noise reduction function, reduce the compressor and fan speeds, and improve the user experience.

[0056] In this embodiment, the data analysis module 2 is communicatively connected to the router, and a first detection area is formed between the data analysis module 2 and the router. A strong magnetic field is constructed between the router and the data analysis module 2 of the refrigerator. The first detection area is the aforementioned strong magnetic field. When a human body is in the magnetic field, it will cause changes, thereby realizing human body sensing. By continuously detecting within the area, it is determined whether there is a person near the refrigerator. The acquisition module 1 is further configured to: acquire CSI data within the first detection area. The data analysis module 2 is further configured to: calculate human activity value based on the CSI data. If the human activity value is greater than the human activity threshold, the refrigerator is controlled to operate in noise reduction mode. The CSI data is acquired through a CSI sensor located on the outside of the refrigerator. The CSI data is used to obtain information such as signal scattering, environmental attenuation, and distance attenuation. Human activity values ​​can be obtained from this information. It is understood that when a user moves into the first detection area formed between the data analysis module 2 and the router, the strong magnetic field will change to a certain extent. For example, changes in signal scattering, environmental attenuation, and distance attenuation caused by changes in the signal transmission path will lead to the determination that a user has appeared in the first detection area. This triggers the refrigerator's noise reduction mode, reducing the speed of the compressor and fan.

[0057] For example, CSI (Channel State Information) data plays a crucial role in the field of wireless communication, and is widely used to analyze key information such as signal scattering characteristics, environmental attenuation, and distance attenuation. This information is not only an important indicator for evaluating wireless communication performance, but also the foundation for monitoring and responding to human activity in smart home environments. CSI data can capture subtle changes in wireless signals caused by human movement or presence. These changes include dynamic adjustments to the signal transmission path, alterations in signal scattering patterns, attenuation caused by environmental absorption and reflection, and the natural attenuation of signals with increasing distance.

[0058] Human activity values ​​are indirectly obtained by analyzing CSI data, enabling precise perception of user dynamics within the home environment. When a user moves into the first detection area jointly defined by data analysis module 2 and the router, the strong magnetic field environment changes due to human interference with wireless signals. These changes manifest as bending, refraction, or reflection along the signal transmission path, and the resulting changes in signal scattering patterns. Simultaneously, the environment's absorption of signals may be enhanced by the human body acting as a new obstacle, leading to increased signal attenuation. Furthermore, as the distance between the user and the router decreases or changes, signal strength attenuates according to the inverse square law of distance; this attenuation information is also accurately recorded. By capturing the CSI data changes caused by user movement through data analysis module 2, the system can quickly determine the presence of human activity within the first detection area, thereby controlling the compressor and fan inside the refrigerator to adjust to lower speeds, effectively reducing noise and providing users with a quieter and more comfortable living environment.

[0059] In this embodiment, the first detection area is the area above a preset height between the data analysis module 2 and the router. In this embodiment, to prevent interference from pets in the user's home, a height threshold is set. For example, only when the height is greater than 1m and a change in the magnetic field is sensed will an instruction be generated to reduce the speed of the compressor and fan to a preset value. It is understood that some users currently keep pets in their homes. To prevent the refrigerator from misjudging the situation when a pet moves near it, a height threshold is set to avoid the system targeting the pet for analysis.

[0060] In this embodiment, the data analysis module 2 is further configured to: determine whether the refrigerator door is open based on the refrigerator door opening / closing data; if the refrigerator door is open, control the refrigerator to operate in noise reduction mode. The refrigerator door switch is located inside the refrigerator compartment, and can be opened or closed by opening or closing the refrigerator door. When the refrigerator door switch is open, it indicates that the refrigerator door is open, meaning the user is in front of the refrigerator door, and directly triggers the refrigerator to operate in noise reduction mode. This function serves as a barrier to ensure the normal functioning of the noise reduction mode when the CSI data detection function is damaged or fails.

[0061] In this embodiment, the acquisition module 1 is further configured to: acquire temperature and humidity values ​​inside the refrigerator; the data analysis module 2 is further configured to: determine whether the fluctuation value of the temperature or humidity value within a first preset time period is greater than a temperature threshold or a humidity threshold, based on the temperature and humidity values; if so, control the refrigerator to operate in noise reduction mode. In this embodiment, the temperature and humidity values ​​are acquired by a temperature sensor and a humidity sensor, which are located inside the freezer compartment. It is understood that the temperature and humidity inside the freezer compartment are low. When the user opens the freezer compartment door, the temperature and humidity inside the freezer compartment will change slightly. This change is measured and set as a temperature threshold or a humidity threshold. The humidity and temperature values ​​inside the freezer compartment are acquired in real time by the temperature and humidity sensors. If the fluctuation value of either the humidity or temperature value is greater than the temperature threshold or the humidity threshold, it indicates that the user has opened the freezer compartment door, and the refrigerator's noise reduction mode is triggered. The above function serves as a barrier to ensure the normal functioning of the noise reduction mode when the CSI data detection function is damaged or fails.

[0062] In this embodiment, the acquisition module 1 is further configured to: acquire the light intensity within a second detection area; the second detection area is the detection area of ​​a light intensity sensor, which is located outside the refrigerator; the data analysis module 2 is further configured to: based on the light intensity, determine whether the fluctuation value of the light intensity within a second preset time period is greater than a light intensity threshold; if so, control the refrigerator to operate in noise reduction mode. The light intensity is acquired by a light intensity sensor, which is located outside the refrigerator and is used to acquire the light intensity within the second detection area; it can be understood that when a user passes through the second detection area, the light intensity within the second detection area will decrease. By acquiring the light intensity within the second detection area in real time, if the fluctuation value of the light intensity is greater than the light intensity threshold, it indicates that the user has passed through the second detection area, thus triggering the refrigerator's noise reduction function.

[0063] In this embodiment, the data analysis module 2 is further configured to: acquire the sound intensity outside the refrigerator based on audio data; determine whether the sound intensity is greater than a sound intensity threshold; if so, control the refrigerator to operate in noise reduction mode. The audio data is acquired through an audio acquisition device located outside the refrigerator for acquiring audio data from the outside of the refrigerator; it is understood that when a user passes by the refrigerator, a certain amount of sound will be emitted, and when the sound intensity reaches the sound intensity threshold set by the data analysis module 2, the refrigerator's noise reduction function is triggered.

[0064] In this embodiment, the data analysis module 2 is further configured to: acquire module start / stop commands; and control the noise reduction mode to turn off according to a set time based on the module start / stop commands. The start / stop commands are input through the refrigerator's display panel to control the noise reduction mode to turn off according to the set time. It is understood that if the system is constantly collecting and analyzing data while the user is sleeping or away from home for extended periods, it will lead to unnecessary power waste. Therefore, the user can input start / stop commands through the display panel to make the refrigerator turn off within a set time. For example, when the user is sleeping at night or traveling for a long time, they can manually turn off the system's noise reduction mode function to avoid unnecessary power consumption.

[0065] In this embodiment, the data analysis module 2 is further configured to perform preprocessing operations on the comparative data. The preprocessing operations include denoising, filtering, and standardization. Denoising aims to remove noise components from the data. This noise originates from measurement errors, equipment malfunctions, environmental factors, etc., which can interfere with the true signal of the data and affect the accuracy of the analysis results. This can be achieved through mathematical filtering (e.g., mean filtering, median filtering), statistical methods (e.g., Kalman filtering), or machine learning algorithms (e.g., outlier detection and removal). Filtering aims to retain useful signals in the data while removing unwanted frequency components. In comparative data analysis, this helps extract key features and reduces data complexity. Filtering operations can select appropriate filters based on the frequency characteristics of the data, such as low-pass filters (retaining low-frequency components and removing high-frequency noise), high-pass filters (retaining high-frequency components and removing low-frequency interference), or band-pass filters (retaining only signals within a specific frequency range). Standardization aims to transform the data to a common scale, enabling comparison and combination between different variables or datasets. This helps eliminate the influence of dimensional differences on the analysis results and improves the generalization ability of the model. Common methods for standardization operations include: min-max scaling, Z-score standardization, etc.

[0066] The packet loss rate and signal strength of the CSI data are obtained. If the packet loss rate or signal strength of the CSI data is less than the packet loss rate threshold or the signal strength threshold, the CSI data is deleted. Because CSI detection can be affected by various factors, such as environmental interference and signal attenuation, efficient data processing and filtering are necessary to ensure the accuracy of the analysis results. The signal strength and packet loss rate values ​​can be used to determine whether the CSI detection results are suitable for noise reduction mode selection.

[0067] Depend on Figure 2This application provides an intelligent noise-reducing refrigerator. Users activate the intelligent noise reduction function, and all sensors collect data in real time (CSI, refrigerator door open / close, temperature and humidity, light intensity, and audio data) and transmit it to the data analysis module 2. The relevant data undergoes preprocessing, such as noise reduction, filtering, and standardization, to ensure data accuracy. For example, if the CSI packet loss rate or signal strength does not reach a threshold, the CSI data is discarded; if it reaches the threshold, the next step is performed. The CSI detection, door open / close, and audio data are analyzed, calculated, and stored in the data analysis module 2. Data collection and analysis are conducted one week before the refrigerator is powered on. On the first day after one week, noise reduction is implemented during the time period indicated in the data analysis results when the user is likely to be near the refrigerator, adjusting the compressor and fan speeds. Every day after the refrigerator is powered on for one week, the data analysis module 2 performs statistical calculations based on all previously collected data and executes new noise reduction rules on the second day, such as setting various thresholds for the collected data.

[0068] A second aspect of this application provides a control method for an intelligent noise-reducing refrigerator, applied to an intelligent noise-reducing refrigerator as described in any of the above embodiments, comprising: collecting comparison data; the comparison data includes: CSI, refrigerator door open / close, temperature and humidity, light intensity, and audio data; determining whether the comparison data is greater than a data threshold; if so, controlling the refrigerator to operate in noise-reducing mode; when the refrigerator operates in noise-reducing mode, the compressor and fan speeds are reduced to preset values. The effects of the above method embodiments can be found in the effects of the above system embodiments, and will not be repeated here.

[0069] The above detailed embodiments further illustrate the purpose, technical solution, and beneficial effects of the embodiments of this application. It should be understood that the above are merely specific embodiments of the embodiments of this application and are not intended to limit the protection scope of the embodiments of this application. Any modifications, equivalent substitutions, improvements, etc., made on the basis of the technical solutions of the embodiments of this application should be included within the protection scope of the embodiments of this application.

Claims

1. A smart noise reduction refrigerator, characterized by, The application relates to a refrigerator noise reduction mode control method and device. The application comprises: A collection module (1) arranged on a box body and configured to: Collect contrast data; the contrast data comprises: CSI, refrigerator door switch, temperature and humidity, light intensity, and audio data; A data analysis module (2) in communication connection with the collection module (1), and electrically connected with a compressor and a fan; the data analysis module (2) is configured to: Determine whether the contrast data is greater than a data threshold value; If yes, control the refrigerator to operate in a noise reduction mode; when the refrigerator operates in the noise reduction mode, the rotation speed of the compressor and the fan is reduced to a preset value; The collection module (1) is further configured to: Collect temperature and humidity values in the box body; The data analysis module (2) is further configured to: According to the temperature and humidity values, determine whether the fluctuation value of the temperature or the humidity within a first preset time is greater than a temperature threshold value or a humidity threshold value; If yes, control the refrigerator to operate in the noise reduction mode; this configuration is a barrier for guaranteeing the normal function of the noise reduction mode when the CSI data detection function is damaged or fails; The data analysis module (2) is further configured to: Obtain a module start-stop instruction; 2. The intelligent noise reduction refrigerator according to claim 1, characterized in that, According to the module start-stop instruction, control the noise reduction mode to be closed according to a set time. The data analysis module (2) is in communication connection with a router, and a first detection area is formed between the data analysis module (2) and the router; The collection module (1) is further configured to: Collect CSI data in the first detection area; The data analysis module (2) is further configured to:

3. The intelligent noise reduction refrigerator according to claim 2, characterized in that, According to the CSI data, calculate a human activity value, and if the human activity value is greater than a human activity threshold value, control the refrigerator to operate in the noise reduction mode.

4. The intelligent noise reduction refrigerator according to claim 1, wherein, The first detection area is an area above a preset height between the data analysis module (2) and the router. The data analysis module (2) is further configured to: According to refrigerator door switch data, determine whether a refrigerator door body is opened; 5. The intelligent noise reduction refrigerator according to claim 1, wherein, If the refrigerator door body is opened, control the refrigerator to operate in the noise reduction mode. The collection module (1) is further configured to: Collect light intensity in a second detection area; the second detection area is a detection area of a light intensity sensor, and the light intensity sensor is arranged outside the box body; The data analysis module (2) is further configured to: According to the light intensity, determine whether the fluctuation value of the light intensity within a second preset time is greater than a light intensity threshold value; 6. The intelligent noise reduction refrigerator according to claim 1, wherein, If yes, control the refrigerator to operate in the noise reduction mode. The data analysis module (2) is further configured to: According to audio data, obtain sound intensity outside the box body; According to the sound intensity, determine whether the sound intensity is greater than a sound intensity threshold value; 7. The intelligent noise reduction refrigerator according to claim 1, wherein, If yes, control the refrigerator to operate in the noise reduction mode. The data analysis module (2) is further configured to: Perform a preprocessing operation on the contrast data; the preprocessing operation comprises: denoising, filtering, and standardization operation; Obtain a packet loss rate and signal strength of the CSI data; If the packet loss rate or the signal strength of the CSI data is less than the packet loss rate threshold or the signal strength threshold, the CSI data is deleted.

8. A control method of a smart noise reduction refrigerator, applied to the smart noise reduction refrigerator of any one of claims 1 to 7, characterized in that, Comprise: Collecting contrast data; The contrast data comprises: CSI, refrigerator door switch, temperature and humidity, light intensity, audio data; Obtaining whether the contrast data is greater than a data threshold value; If yes, control the refrigerator to run in a noise reduction mode; when the refrigerator runs in the noise reduction mode, the compressor and the fan speed are reduced to a preset value.

Images